In a method for dividing an image area in the existing technology, various differential operators may generally be used and a threshold method is further combined to find an area in an image. Specifically, in the method for dividing an image area by setting a threshold and further combining various differential operators, because generally such a method is relatively sensitive to noise in an image, a susceptibility to interference from noise in an image is high in a process of dividing a area; moreover, in the method, a fixed threshold is used, and therefore, when a manner of setting a threshold and further combining various differential operators is used to perform area division on an image, obtained image areas are relatively general, and levels among the image areas are unclear; meanwhile, a problem of segmenting an area having relatively smooth colors also cannot be solved.
In addition, a method of image area growing and area combination in the existing technology may further be used, and descriptions of adjacent areas are compared. For example, parameter descriptions such as average values and variances of two areas may be obtained from the statistics on a grayscale feature. If it is obtained through calculation that two areas match, the two areas are combined into one area, and an area parameter after combination is calculated again. If a calculation result is that two areas do not match, it is marked that the two areas do not match. The step is repeated until all sub-image areas of an image are acquired. In the solution, because a small area having an indistinct feature cannot be inhibited, a susceptibility to interference from noise is also very high. For example, for an area that is relatively smooth in an image of a face portion, area division may fail.
For a problem in related technologies that a smooth area cannot be accurately divided from an image because an image area having an indistinct feature cannot be inhibited, so far no effective solution has been proposed.